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Record W2074460297 · doi:10.3109/17453674.2011.652885

The effect of adding tobramycin to Simplex P cement on femoral stem micromotion as measured by radiostereometric analysis

2012· article· en· W2074460297 on OpenAlexaff
Éric Bohm, Martin J. Petrak, Trevor C. Gascoyne, Thomas R. Turgeon

Bibliographic record

VenueActa Orthopaedica · 2012
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsUniversity of ManitobaConcordia Hospital
FundersStryker
KeywordsMedicineTobramycinOrthopedic surgeryCementBone cementSurgeryOrthodonticsDentistryAntibiotics

Abstract

fetched live from OpenAlex

BACKGROUND: Previous in vitro research on addition of antibiotics to bone cement has found no statistically significant deterioration in mechanical properties. However, no clinical studies have compared the performance of tobramycin-laden bone cement with that of standard bone cement (Simplex P). PATIENTS AND METHODS: 23 patients (25 hips) were randomized to receive an Exeter (Stryker Orthopaedics) femoral stem cemented with either Simplex P (standard) or Simplex T (tobramycin-laden) cement. There were 2 years of follow-up, with scheduled radiostereometric (RSA) examinations. RESULTS: All stems migrated distally and showed some degree of retroversion. No clinically significant differences in stem subsidence or retroversion were found between the Simplex T and Simplex P cement groups after 2 years. Overall subsidence was less than in previous studies, probably due to a postponed initial post-surgical examination. Rates of subsidence in both cement groups were consistent with those from previous studies of Exeter stems. INTERPRETATION: Subsidence of the femoral stem after 2 years was similar in the Simplex T (tobramycin-laden) and Simplex P (standard) groups.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.285
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2012
Admission routes1
Has abstractyes

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